AfterQuerySan Francisco, CAResearch Scientist running controlled SFT and RL experiments to prove the impact of curated datasets on foundation model behavior, generalization, and alignment. Ideal for strong undergrad or master's researchers with deep obsession over data-driven model improvements.
Researcher designing and running experiments on chain-of-thought monitorability in frontier LLMs to support scalable oversight and alignment. Requires strong empirical ML expertise with LLMs, deep interest in model behavior/alignment/interpretability, and ability to translate ambiguous questions into concrete experiments.
As a Simulation Researcher/Engineer, you will design and build simulation environments for training general-purpose robot policies. This role involves working with generative models and classical physics simulation, developing differentiable pipelines, and driving asset generation.
As a Research Scientist on the World Models team, you will invent next-generation world model architectures with a focus on controllability and physical consistency, develop controllability mechanisms, and define and own metrics for physical fidelity and action-following.
Senior researcher studies how training choices shape aligned behavior in frontier models, developing synthetic data, evaluation loops, and experiments to ensure durable, robust tendencies like honest reasoning and instruction-following.
Designs and runs experiments to improve AI model intent alignment, honesty, calibration, and robustness using RL and empirical ML methods. Trains/evaluates large models like LLMs and integrates techniques into production workflows.